Available chart types
Charts allow you to visualize and analyze your process data based on comparisons between categories, over a time period, and by frequency distribution. Charts can be added to your views and configured to suit your data and use cases.
For an overview of how to create charts, see: Charts.
When creating views in Studio, you can add and configure the following chart types:
Category charts
These types of charts are used to show categorical information, allowing for easy comparisons, identifying patterns, and exploring relationships within the data.
Bar
A Bar chart is the simplest version of a categorical chart. It offers a clear visual representation that facilitates easy comparison between different categories, making trends and patterns readily identifiable.
The categorical bar chart is horizontal because it can more easily support longer category labels without overcrowding labels and bars. The horizontal bars also more naturally emphasize the values represented by the length of the bars. While we don’t recommend it, you can still use categorical data in the vertical column chart as well.
Minimum data required: 1 x categorical dimension, 1 x metric.
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Stacked Bar
Stacked bar charts with two metrics are useful when you need to visualize the composition of a whole (total) in relation to two different contributing factors.
Currently, you can only sort each KPI individually. Sorting based on the total bar length is coming soon.
Minimum data required: 1 x categorical dimension, 2 x metrics.
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Grouped Bar
Choose a grouped bar chart with two metrics when you want to compare the values of two metrics across different categories, maintaining clarity in distinguishing between the metrics.
Minimum data required: 1 x categorical dimension, 2 x metrics.
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Pie and Donut
Pie charts can be great when you want to display simple data distributions with a few categories and emphasize the proportions of each category relative to the whole.
Pie charts can become very hard to read if you have too many slices. If you need more than 5 slices then a bar chart would be a better visualization for you.
Minimum data required: 1 x categorical dimension, 1 x metric.
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Additional category charts
The following category charts will be supported soon: Grouped Bar Chart with 2 Dimensions, Stacked Bar Chart with 2 Dimensions, Scatterplot, Treemap, Bubble.
Time series charts
Time series charts display data points or values along a continuous time axis. They usually help show how a particular KPI(s) has changed over time. All time series charts are based on a horizontal axis because it aligns with the natural progression of time from left to right.
Line
A line chart is the best time series chart to understand continuous trends.
You will notice that you can not sort a line chart. This is intentional since This type of chart is a time series chart, meaning that it is intended to visualize how a metric changes over time, and introducing sorting could potentially distort the representation, leading to zigzag patterns and undermining the clarity of the data.
Minimum data required: 1 x time dimension, 1 x metric.
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Column
Avoid using the vertical bar chart for categorical dimensions.
We naturally read time data from left to right, therefore it is better to use column charts over bar charts for these cases. Check out bar charts for better category-based visualizations.
Minimum data required: 1 x time dimension, 1 x metric.
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Additional time series charts
The following time series charts will be supported soon: Grouped Column with 2 Dimensions, Stacked Column with 2 Dimensions, Column and Line.
Distribution charts
These chart types allow you to how the distribution of data cross a range.
Histogram
Histograms are best used when you want to understand the distribution or frequency of data within a continuous range, such as cycle times, defect rates, or the number of days past a due date.
Minimum data required: 1 x numeric dimension.
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Chart coloring
You have the following chart coloring options:
Color based on a dimension
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Color based on a metric
When coloring your column, KPI, or chart mark based on a metric, you can choose to color with a gradient or threshold color mapping based on the story you are trying to tell.
You can also use create diverging color rule by adding a center value. Instead of only going from low to high, they have a center value.
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Thresholds should be used when you want to highlight or emphasize a certain segment of your data.
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Chart color best practice
When configuring your chart colors, we recommend the following best practice:
Consistency: Don’t change the meaning of colors across views. Be consistent in the use of colors, ensuring that your viewers are able to quickly identify the meaning behind the colors you've used.
Use color to emphasize or de-emphasize points: While colors can be powerful, they are often overly utilized, making it even more challenging for users to identify insights. Use color to focus attention on what matters.
A good example of this:
Unnecessary coloring: Avoid the over-use of colors for charts where there are no visual benefits to using them.
A good example of a chart where using one default color works best:
And the same chart but with unnecessary coloring:
Sequential color scales often increase comprehension: When coloring continuous categories, gradient colors are often much easier to read than using multiple hues.
The gradient color clearly indicates more or less contribution:
In this example using hues for each category does not create any value for the user:
Mixing colors: Don’t mix high and low saturated colors unless you are trying to show the importance or ordering.